Developing a Strategic Competitive Intelligence Framework for Decision-Making in VUCA Environments

Abstract

Abstract
This study investigates the growing importance of strategic decision-making in VUCA environments. It fills an important gap in the existing literature: the lack of a comprehensive framework that incorporates strategic management principles and competitive intelligence to respond effectively and overcome VUCA challenges. Such integration of strategic management and competitive intelligence has emerged as a key driver for triumphing over challenges posed by VUCA. Strategic management provides a forward-looking and visionary framework for conceptualising organisational direction and proactive allocation of resources, and competitive intelligence offers mechanisms to anticipate trends, decipher complexities, and create actionable insights into the competitive environment. This enables organisations to move beyond reactive responses and instead proactively shape and influence their context. The study’s primary objective is to develop, evaluate and validate the Strategic Competitive Intelligence (SCI) framework as an innovative model designed to empower organisations to successfully navigate and address VUCA challenges. Employing a mixed-methods approach, the research is structured into two phases. Phase one integrates a survey with both quantitative and qualitative components targeting Competitive Intelligence (CI) professionals and Chartered Managers (CMs). Phase two involves an online interactive workshop that incorporates a real-world VUCA scenario. Key findings reveal an ongoing dependence on conventional analytical tools including but not limited to SWOT, PESTLE, and Porter's Five Forces when addressing VUCA challenges despite their acknowledged limitations in highly dynamic context. These traditional frameworks are used to examine the individual components of VUCA in isolation rather than holistically. In contrast, the proposed SCI framework put forth in this research aims to tackle the multifaceted aspects of VUCA in a more integrated, comprehensive fashion. A significant shift towards advanced intelligence tools and techniques (AITTs) such as automated weak signal detection, advanced modelling techniques, data mining and processing, predictive forecasting, inter alia, has been observed when practitioners confront tangible VUCA challenges. Additionally, practitioners have expressed strong support for the SCI framework and its structured approach, underpinned by the concept of the VUCA chain reaction effect (VUCA CRE). The research has significant implications for both theory and practice. It proffers a novel framework designed to enhance strategic decision-making under VUCA environments and provide practical guidance for CI professionals and CMs. It also lays the groundwork for creating an easy-to-use SCI application with AI-integrated features. This research opens exciting possibilities both for expanding theories on strategic decision-making in VUCA environments, as well as giving practical help to professionals in the field.

Date of Award	30 Apr 2025
Original language	English
Awarding Institution	University of Portsmouth
Supervisor	Mark Xu (Supervisor), Alessio Ishizaka (Supervisor) & Salem Chakhar (Supervisor)